This section is intended to introduce the reader to various aspects of art, which may be related to various aspects of the present invention that are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present invention. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art.
Video annotation is very useful for various applications, such as for example hiding or blurring moving objects for censuring purposes. It is also very useful for generating a ground truth in order to evaluate object detection algorithms in computer vision, both for training the algorithm and for testing its performance. A straight forward approach is to manually annotate each frame of a video sequence, but it can be very tedious and time consuming. When the object to annotate is pretty static, or when its shape does not vary along a video sequence, some prior art methods are known wherein a few frames are annotated and the trajectory of the object is tracked. For example U.S. Pat. No. 7,911,482 “Method and system for efficient annotation of object trajectories in image sequences” discloses a method for annotating an object in a video. The method comprises an initial temporal subsampling of the video sequence is initially performed. The subsampled image sequence is displayed in two orthogonal directions across an interactive screen. A user draws two orthogonal trajectories by tracking the object to annotate across the two orthogonal subsampled sequences via the interactive screen. The method further describes obtaining a neo trajectory that is further interpolated to the rest of the video sequence. However such method fails in precisely annotating objects of varying size and shape along a video sequence. Indeed, although the prior art methods can capture a moving object trajectory they are not able to adapt the size of the annotated region of each frame of the video to the varying size/shape of the object to annotate. Therefore, some new efficient methods are needed for automatically annotating moving objects of varying size and/or shape in video sequences, without requiring to manually edit and annotate every frame.